Sharding-Jdbc分库分表的导读

2021-09-20 03:23:47

前言

Sharding-JDBC是一个开源的分布式数据库中间件，它无需额外部署和依赖，完全兼容JDBC和各种ORM框架。Sharding-JDBC作为面向开发的微服务云原生基础类库，完整的实现了分库分表、读写分离和分布式主键功能，并初步实现了柔性事务。

以2.0.3为例maven包依赖如下

<project xmlns="http://maven.apache.org/POM/4.0.0"
    xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
    xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
    <modelVersion>4.0.0</modelVersion>

    <groupId>com.dongpeng</groupId>
    <artifactId>sharding-jdbc</artifactId>
    <version>1.0.0</version>
    <packaging>jar</packaging>

    <name>sharding-jdbc</name>
    <url>http://maven.apache.org</url>

    <properties>
        <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
    </properties>

    <dependencies>
        <dependency>
            <groupId>io.shardingjdbc</groupId>
            <artifactId>sharding-jdbc-core</artifactId>
            <version>2.0.3</version>
        </dependency> 
        <dependency>
            <groupId>com.google.guava</groupId>
            <artifactId>guava</artifactId>
            <version>23.0</version>
        </dependency>
        <dependency>
            <groupId>com.mchange</groupId>
            <artifactId>c3p0</artifactId> 
            <version>0.9.5.2</version>
        </dependency>
        <dependency>
            <groupId>mysql</groupId>
            <artifactId>mysql-connector-java</artifactId>
            <version>5.1.46</version>
        </dependency>
        <dependency>
            <groupId>log4j</groupId>
            <artifactId>log4j</artifactId>
            <version>1.2.17</version>
        </dependency>
        <dependency>
            <groupId>org.slf4j</groupId>
            <artifactId>slf4j-api</artifactId>
            <version>1.7.21</version>
        </dependency> 
        <dependency>
            <groupId>org.slf4j</groupId>
            <artifactId>slf4j-log4j12</artifactId>
            <version>1.7.21</version>
        </dependency>

    </dependencies>
    <build>
        <resources>
            <resource>
                <directory>src/main/java</directory>
            </resource>
            <resource>
                <directory>src/main/resources</directory>
            </resource>
        </resources>
        <plugins>

            <plugin>
                <groupId>org.apache.maven.plugins</groupId>
                <artifactId>maven-compiler-plugin</artifactId>
                <configuration>
                    <source>1.8</source>
                    <target>1.8</target>
                    <encoding>UTF-8</encoding>
                </configuration>
            </plugin>
        </plugins>
    </build>
</project>

简单的分库demo介绍如下

package com.dongpeng.sharding.jdbc;

import java.sql.Connection;
import java.sql.PreparedStatement;
import java.sql.ResultSet;
import java.util.HashMap;
import java.util.Map;
import java.util.Properties;

import javax.sql.DataSource;

import com.mchange.v2.c3p0.ComboPooledDataSource;

import io.shardingjdbc.core.api.ShardingDataSourceFactory;
import io.shardingjdbc.core.api.config.ShardingRuleConfiguration;
import io.shardingjdbc.core.api.config.TableRuleConfiguration;
import io.shardingjdbc.core.api.config.strategy.InlineShardingStrategyConfiguration;

/**
 * sharding-jdbc分库的demo
 * @author Admin
 *
 */
public class ShardingDataDemo {
    public static void main(String[] args) throws Exception{

        Map<String, DataSource> dataSourceMap = new HashMap<String, DataSource>();
        ComboPooledDataSource dataSource1 = new ComboPooledDataSource();
        dataSource1.setDriverClass("com.mysql.jdbc.Driver"); // loads the jdbc driver
        dataSource1.setJdbcUrl("jdbc:mysql://localhost:3306/db_0?useSSL=false");
        dataSource1.setUser("root");
        dataSource1.setPassword("root");
        dataSourceMap.put("db_0", dataSource1);
        
        ComboPooledDataSource dataSource2 = new ComboPooledDataSource();
        dataSource2.setDriverClass("com.mysql.jdbc.Driver"); // loads the jdbc driver
        dataSource2.setJdbcUrl("jdbc:mysql://localhost:3306/db_1?useSSL=false");
        dataSource2.setUser("root");
        dataSource2.setPassword("root");
        dataSourceMap.put("db_1", dataSource1);
        
        /**
         * 配置分库规则
         */
        TableRuleConfiguration orderTableRuleConfig = new TableRuleConfiguration();
        orderTableRuleConfig.setLogicTable("t_order");
        orderTableRuleConfig.setActualDataNodes("db_${0..1}.t_order_0");
        orderTableRuleConfig.setDatabaseShardingStrategyConfig(new InlineShardingStrategyConfiguration("user_id", "db_${user_id % 2}"));
        
        /**
         * 分片规则配置
         */
        ShardingRuleConfiguration shardingRuleConfig = new ShardingRuleConfiguration();
        shardingRuleConfig.getTableRuleConfigs().add(orderTableRuleConfig);
        Properties properties = new Properties();
        properties.put("sql.show", "true"); 
        DataSource dataSource = ShardingDataSourceFactory.createDataSource(dataSourceMap, shardingRuleConfig,new HashMap<String,Object>(),properties);
        Connection connection  = dataSource.getConnection();
        PreparedStatement statement =  connection.prepareStatement("select * from t_order where user_id=?");
        
        statement.setInt(1, 1);
        ResultSet rs = statement.executeQuery();
        while(rs.next()) {
            System.out.println(rs.getString("user_id"));
        }
        rs.close();
        statement.close();
        connection.close();
        
       
    
    }
}

几个重要的类

ShardingRuleConfiguration

ShardingDataSourceFactory

ShardingDataSource

ShardingConnection

ShardingPreparedStatement

ShardingStatement

源码分析

ShardingRuleConfiguration

分片的规则配置类主要的属性如下

    private String defaultDataSourceName;
    
    private Collection<TableRuleConfiguration> tableRuleConfigs = new LinkedList<>();
    
    private Collection<String> bindingTableGroups = new LinkedList<>();
    
    private ShardingStrategyConfiguration defaultDatabaseShardingStrategyConfig;
    
    private ShardingStrategyConfiguration defaultTableShardingStrategyConfig;
    
    private String defaultKeyGeneratorClass;
    
    private Collection<MasterSlaveRuleConfiguration> masterSlaveRuleConfigs = new LinkedList<>();

defaultDataSourceName指定没有分片规则库使用的数据源

tableRuleConfigs 配置指定表的分片规则

TableRuleConfiguration的属性如下

    private String logicTable;
    
    private String actualDataNodes;
    
    private ShardingStrategyConfiguration databaseShardingStrategyConfig;
    
    private ShardingStrategyConfiguration tableShardingStrategyConfig;
    
    private String keyGeneratorColumnName;
    
    private String keyGeneratorClass;
    
    private String logicIndex;

logicTable配置逻辑表比如数据库中有t_order_0,t_order_1两张表，逻辑表设置为t_order

actualDataNodes逻辑节点配置,用的类InlineExpressionParser作为解析器，配置如 db_${0..1}.t_order_0

databaseShardingStrategyConfig配置数据库的分片规则

tableShardingStrategyConfig 表的分片规则

两个分片规则都实现了ShardingStrategyConfiguration接口，用于构建ShardingStrategy分片类,以下是sharding-jdbc提供的分片配置类，具体实现分片规则可以查看源码

keyGeneratorColumnName配置分布式主键

keyGeneratorClass配置id生成类

logicIndex配置逻辑分片索引位置

还有properties,map的方式配置一些信息这个可参考文档，如sql.show在properties中配置等等

ShardingDataSourceFactory

shardingDataSourceFactory是ShardingDataSource的工厂类，用于创建ShardingDataSource生成方式

支持文件，自定义等等如下

public static DataSource createDataSource(final Map<String, DataSource> dataSourceMap, final ShardingRuleConfiguration shardingRuleConfig, 
                                              final Map<String, Object> configMap, final Properties props) throws SQLException {
        return new ShardingDataSource(shardingRuleConfig.build(dataSourceMap), configMap, props);
    }
    
    /**
     * Create sharding data source.
     *
     * @param yamlFile yaml file for rule configuration of databases and tables sharding with data sources
     * @return sharding data source
     * @throws SQLException SQL exception
     * @throws IOException IO exception
     */
    public static DataSource createDataSource(final File yamlFile) throws SQLException, IOException {
        YamlShardingConfiguration config = unmarshal(yamlFile);
        return new ShardingDataSource(config.getShardingRule(Collections.<String, DataSource>emptyMap()), config.getShardingRule().getConfigMap(), config.getShardingRule().getProps());
    }

ShardingDataSource

主要用于初始化构建dataSource的一些配置信息封装成ShardingContext提供给ShardingConnection使用

ShardingConnection

继承自AbstractConnectionAdapter同时实现了connection接口，封了preparedStatement和statement的调用方法，ShardingPreparedStatement和ShardingStatement类来实现,主要的方法是获取connection的方法如下

    public Connection getConnection(final String dataSourceName, final SQLType sqlType) throws SQLException {
        if (getCachedConnections().containsKey(dataSourceName)) {
            return getCachedConnections().get(dataSourceName);
        }
        DataSource dataSource = shardingContext.getShardingRule().getDataSourceMap().get(dataSourceName);
        Preconditions.checkState(null != dataSource, "Missing the rule of %s in DataSourceRule", dataSourceName);
        String realDataSourceName;
        if (dataSource instanceof MasterSlaveDataSource) {
            NamedDataSource namedDataSource = ((MasterSlaveDataSource) dataSource).getDataSource(sqlType);
            realDataSourceName = namedDataSource.getName();
            if (getCachedConnections().containsKey(realDataSourceName)) {
                return getCachedConnections().get(realDataSourceName);
            }
            dataSource = namedDataSource.getDataSource();
        } else {
            realDataSourceName = dataSourceName;
        }
        Connection result = dataSource.getConnection();
        getCachedConnections().put(realDataSourceName, result);
        replayMethodsInvocation(result);
        return result;
    }

这个方法的作用是，如果拿到的数据源是一个MasterSalveDataSource的数据源，需要进行读写分离的判断，并最终返回执行的connection

ShardingPreparedStatement和ShardingStatement

具体的执行类，都有对应的route方法封装最终都交由SQLRouter来解析sql获取最终的路由信息，最后执行相应的sql

码农公寓

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